AI is on full rage nowadays. We are seeing how Zuckerberg is making J.A.R.V.I.S out of it for the most complex things, and have also witnessed how a startup is claiming to make websites out of it. Everyone is in the ship including the bloggers and influencers who are predicting the future with advancements that we should keep eye on. All in all, we know that AI is going to have a bright future and there are no second thoughts about it.

copyright by

SwissCognitiveAlong with AI, there are two more names we have been listening or reading with in the discussions, ML (Machine Learning) and NLP (Natural Language Processing). People usually get confused between these three terms. The thing is that they are deeply interconnected. In a way, they are almost similar to each other, a perfect example of AI will include a blend of NLP and ML. NLP and ML are the branches of Artificial Intelligence. Allow me to help you in this confusing topic and differentiate between ML, NLP and AI.

Artificial Intelligence

Artificial Intelligence is the process of incorporating human intelligence into machines or computer systems, so that they can develop the ability to think and respond like humans. ML and NLP are the subfields of AI. AI is a broad field and it includes reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. To simplify this, we can say that AI is a program that incorporates the problem-solving abilities of a human and it can perform tasks for humans efficiently. The main goal is Artificial Intelligence is to develop such machines that can make intelligent decisions based on past experiences and their learning abilities and convey it (the solution) to the humans.

Machine Learning

Machine Learning can be defined as an algorithm of making systems learn, by using observations (example data) or past experience. In other words, if you a developing ML in a system, you are building a system that can learn from experience. The models that will be produced in the results can be predictive and they might have the ability to give the future predictions and coming up with intelligent solutions in a specific condition due to their past experiences. Machine learning is not being applied in our daily chatbots and other programs. It is used mainly in complex data problem which humans can resolve but the communication gap doesn’t allow them to do so. This where machine learning kicks in; it provides better solutions to the problems because of its past experiences.

Natural Language Processing

Natural Language Processing is the process of explaining a structure or a command to a machine in the natural language as used by humans; translating it into a format that a machine can understand and process it and generate it back to the user. In other words, developing NLP is like building a system that can understand human language. If you want to make a machine understand a language, the machine should learn how to do it first and this is where we use machine learning within the NLP. […]

read more – copyright by